13 papers
Residual Trajectory Distillation for Generative Retrieval
Weihao Shen, Wei Chen, Fuwei Zhang +4
Generative retrieval has emerged as a general retrieval paradigm, representing items with discrete Semantic IDs (SIDs) and retrieving them through autoregressive identifier generat…
Learning Multiresolution Relevance for Hierarchical Generative Retrieval
Weihao Shen, Wei Chen, Fuwei Zhang +4
Generative retrieval with semantic identifiers (SIDs) makes successive decisions over a document hierarchy. Relevant documents for the same query may share coarse prefixes and dive…
HiTS-CL: A Continual Learning Framework for Long-Horizon Temporal Knowledge Graph Extrapolation
Yansong Liu, Rui Liu, Yuan Zuo +6
Extrapolative temporal knowledge graph reasoning (TKGR) predicts future facts from historical snapshots. Most existing methods train once on an early prefix of the timeline and the…
ICEGR: An Intent-Coherent End-to-End Generative Retrieval Framework for E-commerce Search
Jiayi Tuo, Hehan Li, Dongjun Fu +10
Generative Retrieval (GR) is promising for e-commerce search, yet existing methods struggle to maintain query-intent consistency throughout the training pipeline. First, semantic I…
VisDocAgentBench: Benchmarking Agents for Visually Rich Document Retrieval
Lexiang Hu, Yanzhao Zhang, Mingxin Li +5
Visually rich documents encode relevance through language, layout, structured visual elements, and corpus context, yet retrieval is typically evaluated by one-shot query--page matc…
Requirement--Evidence Alignment for Compositional E-Commerce Queries
Weihao Shen, Wei Chen, Fuwei Zhang +6
Compositional e-commerce queries express multiple requirements that must hold jointly, yet existing rerankers collapse these constraints into aggregate relevance and often promote…
Unpaired Modality-Agnostic Generative Recommendation
Weihao Shen, Wei Chen, Fuwei Zhang +6
Generative Recommendation (GR) formulates recommendation as autoregressive generation over discrete semantic identifiers (IDs). Although recent multimodal GR methods improve semant…
Beyond Matching: Category-Guided Latent Intent Reasoning for Generative Retrieval in E-Commerce
Fuwei Zhang, Xiaoyu Liu, Jiajie Jin +8
Generative retrieval offers a new paradigm for e-commerce search by mapping user queries directly to product Semantic Identifiers (SIDs). However, e-commerce queries are often shor…
CORE-Bench: A Comprehensive Benchmark for Code Retrieval in the Era of Agentic Coding
Fuwei Zhang, Yanzhao Zhang, Mingxin Li +5
Code retrieval is becoming central to coding agents, but agentic coding requires more than matching a natural-language query to an isolated snippet. Given a user request, a coding…
SynGR: Unleashing the Potential of Cross-Modal Synergy for Generative Recommendation
Wei Chen, Xingyu Guo, Shuang Li +6
Generative Recommendation (GR) has emerged as a promising paradigm by formulating item recommendation as a sequence-to-sequence generation task over item identifiers. Recent studie…
LASAR: Latent Adaptive Semantic Aligned Reasoning for Generative Recommendation
Yiwen Chen, Fuwei Zhang, Zehao Chen +7
Large Language Models (LLMs) have demonstrated powerful reasoning capabilities through Chain-of-Thought (CoT) in various tasks, yet the inefficiency of token-by-token generation hi…
Multi-Aspect Cross-modal Quantization for Generative Recommendation
Fuwei Zhang, Xiaoyu Liu, Dongbo Xi +5
Generative Recommendation (GR) has emerged as a new paradigm in recommender systems. This approach relies on quantized representations to discretize item features, modeling users'…
CAT-ID: Category-Tree Integrated Document Identifier Learning for Generative Retrieval In E-commerce
Xiaoyu Liu, Fuwei Zhang, Yiqing Wu +6
Generative retrieval (GR) has gained significant attention as an effective paradigm that integrates the capabilities of large language models (LLMs). It generally consists of two s…